随着节能环保受到日益重视,电网经济调度需同时考虑燃料成本和污染排放2个目标。电力系统多区域环境经济调度是一个复杂的非凸多目标问题,迄今未得到很好解决。基于NW小世界提出了一种新颖的改进纵横交叉算法(NWCSO)。采用容量可动态调整的外部存档集合存储当前Pareto最优解,利用Pareto占优策略确定个体最优位置,进而根据粒子拥挤距离确定全局最优位置。将NWCSO算法应用于16机组4个区域测试系统进行仿真计算,结果表明该算法在解决该多区域多目标问题方面具有优越性。
With increasing emphasis on energy conserva- tion and environmental protection, the fuel cost and emission should be both taken into consideration in the economical dis- patch in the power grid. The multi-area economic/emission dis- patch(MAEED)is a complex non-convex multi-objective problem, which has yet to be well addressed. This paper proposes a novel NW small world network based on the crisscross opti- mization algorithm(NWCSO) for addressing the MAEED problem. The Pareto optimal solution is stored in an external set which is dynamically adjusted by the capacity. The personal best position is determined by using the Pareto dominant strategy and the global optimal position is identified by the crowding distance between particles. The NWCSO approach is validated on a test system consisting of 16 units with four areas considered. The scheduling scheme shows that the algorithm is both feasible and effective in solving the MAEED problem. In addition, the results show that NWCSO algorithm obtains better solution quality than other algorithms in the literature.